MCP Documentation Search

As part of the LlamaIndex documentation, we serve a hosted MCP server that allows any agent to search the LlamaIndex documentation.

The hosted MCP server is available at the following URL:

https://developers.llamaindex.ai/mcp

The server ships with the following tools:

1. search_docs — a basic lexical search using BM25
2. grep_docs — exact search using regex
3. read_doc — provides an interface to read the entire contents of any given page path

Configure your Agent

Cursor

You can click to install to cursor directly or add the following to your mcp.json configuration:

{
  "mcpServers": {
    "llama_index_docs": {
      "url": "https://developers.llamaindex.ai/mcp"
    }
  }
}

Claude Code

Add the documentation search tools to your Claude Code agent with a single command:

claude mcp add llama-index-docs --transport http https://developers.llamaindex.ai/mcp

OpenAI Codex

Add the documentation search tools to your OpenAI Codex agent by adding the following section to your config.toml:

[mcp_servers.llama_index_docs]
url = "https://developers.llamaindex.ai/mcp"

LlamaIndex Agents

Install llama-index and the MCP tools package:

pip install llama-index llama-index-tools-mcp

And then directly use the MCP tools in your agent:

from llama_index.core.agent import FunctionAgent, ToolCall, ToolCallResult
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import McpToolSpec, BasicMCPClient


async def main():
    client = BasicMCPClient("https://developers.llamaindex.ai/mcp")
    tool_spec = McpToolSpec(client=client)
    tools = await tool_spec.to_tool_list_async()

    agent = FunctionAgent(
        llm=OpenAI(model="gpt-4.1", api_key="sk-..."),
        tools=tools,
        system_prompt="You are a helpful assistant that has access to tools to search the LlamaIndex documentation."
    )

    while True:
        query = input("Query: ")
        handler = agent.run(query)
        async for ev in handler.stream_events():
            if isinstance(ev, ToolCall):
                print(f"Calling tool {ev.tool_name} with input {ev.tool_kwargs}")
            if isinstance(ev, ToolCallResult):
                print(f"Tool {ev.tool_name} returned {ev.tool_output}")

        resp = await handler
        print("")
        print(resp)
        print("=================")

if __name__ == "__main__":
    import asyncio
    asyncio.run(main())